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Apple trees tend to bear an excess of young fruits (fruitlets). Chemical thinning with an application of bioregulators early in the season is currently the most common solution to adjust fruit load. However, the results of this approach are highly inconsistent between seasons. In the present study, we identified the most informative bands in the visible-near infrared range for forecasting fruitlet destiny in response to the thinner application, which could be used to support grower decisions. "Golden Delicious" apple trees were monitored during two consecutive seasons, following the application of synthetic auxins commonly used in commercial orchards. Simple bands, band differences, and band ratios were investigated as features for forecasting fruitlet destiny from the first week of monitoring. Optimal threshold values and best wavelengths combinations were determined via the receiver operating characteristic (ROC) curve. At the early stage of fruitlet development (4–6 days after treatment, DAT), applying thresholding to the band difference R 973 − R 404 was preferable (accuracies ranging from 66% to 87%), while applying thresholding to the band ratio R 693 / R 674 was preferable at 7–12 DAT (accuracies ranging from 76% to 95%). The present results indicate that the development of a simplified portable device for forecasting apple fruitlet drop seems feasible. Complimentary measurements performed on intact vs. denuded fruitlets revealed that the spectral differences observed can be explained by substantial changes in trichomes density that occur naturally during fruitlet development and affect the apparent pigment absorption. • Spectral wavebands were investigated to forecast apple fruitlet drop. • Optimal bands were identified with receiver operating characteristic curve. • Two to four optimal bands led to 66–95% accuracy depending on monitoring dates. • Later monitoring dates resulted in higher forecast accuracies. • Trichome density changes strongly affected apple fruitlet reflectance. [ABSTRACT FROM AUTHOR]

A procedure for identifying apples in night-time orchard images was developed and tested on two datasets totalling over 550 images of Golden Delicious trees captured on two years with different cameras and lighting systems. The analysis started by detecting specular reflection highlights and extracting sub-images (101 by 101 pixels) centred at those local maxima. Each sub-image was reduced to a 676 Upright Speeded Up Robust Features (U-SURF) vector. Close to 20,000 sub-images from one dataset were manually labelled as “apple” or “not apple”. The latter group included parts of leaves, branches and other objects which exhibited strong specular reflection. Seventy-two classifiers were trained with the number of “apple” and “not apple” training samples ranging from 500 to 2000 and from 5000 to 10,000, respectively, and with vocabulary size ranging from 500 to 10,000. Misclassifications occurred mostly in dark and low contrast regions, which led to developing alternate models based on the posterior probability that the classification result was correct taking into account the sub-image entropy or intensity. Yield models were calibrated for each dataset, using 20 random trees. For both datasets the overall yield estimate was within 10% of the actual yield, and the standard deviation was around 30% of the average tree yield. These results are similar to those reported in previous studies, but while these previous studies used procedures calibrated and tested with images from the same dataset, in the present study the classifier trained with images from one dataset was successfully applied to the second dataset. [ABSTRACT FROM AUTHOR]

Measurements indicative of crop development, such as leaf area index, canopy cover or biomass are typically performed only a few times throughout the season at irregular time intervals. Furthermore, due to the inherent spatial variability that exists in the field, combining measurements taken at different locations in the field usually leads to large uncertainty around the mean value. These factors, together with the fact that crop-soil models are strongly non-linear, render assimilation of measurements in crop-soil models non-trivial. This work presents procedures for performing such data assimilation, using the crop model AquaCrop as specific example. The procedures are based on Extended Kalman Filter, with some heuristic adjustments, and enable re-initialisation of state variables and/or adjustments of selected parameters of the model. The uncertainties of the measurements are taken into account explicitly in the proposed assimilation scheme. The procedures were tested with data obtained from experiments conducted with potato in Denmark and cotton in Greece. In both cases the data available consisted of canopy cover and biomass (average and standard deviation on 5–10 days), and a locally-calibrated AquaCrop model was used as starting point for the assimilation process. The results demonstrate the soundness of the approach but also emphasise the inherent limitations associated with data assimilation. In particular, assimilation of easy-to-obtain canopy cover measurements did not always improve the predictions of biomass. [ABSTRACT FROM AUTHOR]

This paper details a procedure for detecting apples in tree images using shape analysis are presented. The core of the procedure consists of a so-termed convexity test that identifies edges that could correspond to three-dimensional convex objects of a given size range from a much larger set of edges. This is achieved by analysing a number of intensity profiles that originate at each edge and determining whether they have a shape that is suitable with a 3D convex object of the correct size. We show that contrarily to the prevailing opinion, the intensity functions of three-dimensional convex objects are not necessarily convex, which led us to developing models for describing such profiles. The simplest suitable model includes four parameters that can be easily estimated by a standard least square constrained optimization procedure. After merging the selected edges that fall on circles, a second analysis is performed to remove false positive detections and eliminate multiple detections of apples. The procedure was demonstrated on 51 grey-level images that were recorded in a Golden Delicious apple variety orchard under natural light conditions. On average, together with preliminary pre-processing operations, the convexity test removed 99.8% of the edges initially identified by Canny filter. Analysis based on the remaining edges led to correct detection of 94% of the apples visible in the images. Fourteen percent of the identified objects were “false positive” detections, mainly due to leaves or parts of leaves that generated convex surfaces very similar to apples, or by leaves that lay on apples and created misleading edges. [ABSTRACT FROM AUTHOR]

Non-invasive methods that enable continuous monitoring of spatial and temporal variations of physical and chemical parameters in the roots and the rhizosphere in situ are required in order to study the complex soil–roots interactions. In this work we present the use of laser-induced fluorescence imaging for visualizing these processes. The system consists of a Nd:YAG Q-switched laser that excites the root and rhizosphere auto-fluorescence, and an intensified gated camera (intensified charged coupled device (ICCD)) that is synchronized with the laser so that it captures the very short auto-fluorescence signal even in broad daylight. By using very short gating times (1 ns) and varying the delay between the laser pulse and the gating operation, time-resolved fluorescence profiles are obtained for each pixel in the image. The potential of the system is illustrated with several examples that show that both fluorescence intensity and temporal evolution profiles provide information about root activity and root–soil interactions. [ABSTRACT FROM AUTHOR]

The expansion of an existing crack in chicken eggs exposed to an abrupt pressure drop was investigated. The initial crack was induced in the eggshells by two weak mechanical impacts close enough to induce a macro-crack oriented mainly along the direction of the meridian. The cracked eggs were placed in a custom-made pressure chamber in which the pressure was abruptly decreased to −25 kPa. During this pressure drop, crack expansion was measured using an imaging system and three phases of expansion (evolution of equivalent crack width vs. time) were observed: a linear mode, an exponential mode and a transition zone between them. A model that associates these phases of expansion with the stretching and tearing of the outer membrane is proposed. According to this model, the linear mode corresponds to reversible membrane stretching, which ends with membrane tearing during the transition zone. This model was supported by visual observations that revealed that membrane fragments became visible in the transition zone, and by the crack expansion curves obtained during weaker pressure drops (−10 kPa), which showed that only linear (reversible) crack expansion occurred. It was also shown that the air cell that is initially enclosed between the inner and outer membranes at the egg blunt-end plays in important role in the crack expansion. A simple model of the airflow that escapes from the egg through the crack shows that the airflow from the blunt-end to the crack, rather than the airflow through the crack itself, is the limiting factor. [Copyright &y& Elsevier]

A climate control system for a small greenhouse equipped with a variable-pressure fogging system and variable-speed extracting fans was developed and validated. The controllers were designed using the robust control method quantitative feedback theory (QFT) that guarantees adequate performance of the controlled system despite large modelling uncertainties and disturbances. In order to simplify the design of the controllers and achieve better performances, partial decoupling between the two control loops was achieved by describing the greenhouse climate in terms of air enthalpy and humidity ratio. This led to using ventilation for achieving the desired air enthalpy, and fogging for achieving the desired humidity ratio, assuming that the ventilation rate was approximately known. The implementation results demonstrated the good performance of the controllers, with mean tracking errors of ∼100 J kg−1 [dry air] and ∼0.1 g [water] kg−1 [dry air] for enthalpy and humidity ratio, respectively. For practical applications, the desired climate was expressed in terms of air temperature and relative humidity, which were converted into enthalpy and humidity ratio using the psychrometric relationships. In this case, the mean tracking errors were ∼0.2 °C air temperature and less than 1% relative humidity, and the maximum mean deviations over a 10-min period with constant setpoints were 2.5 °C air temperature and 5% relative humidity. [Copyright &y& Elsevier]

This paper presents a relatively simple approach for determining optimal paths for car-like vehicles operating in orchards. The method relies on the vehicle''s configuration space and uses the well-accepted A* algorithm to determine the optimal path, taking into account constraints that are specific to the type of vehicle and environment considered: limited steering angle, limited range of pitch and roll angles permissible, forward motion preferable, and frequent turning not desirable. All these constraints are expressed as penalty terms weighted via user-defined parameters that reflect the type of path implicitly sought by the user. A number of examples are presented, which show the ability of the procedure to find the optimal path in various situations and illustrate how the weighting parameters can be used to shape the solution. [Copyright &y& Elsevier]

Accurate simulation models for short-term (∼hours) changes in hydroponic crop growth and nitrate uptake are needed for rapid fault detection in hydroponic systems. Comparison between model-predicted and measured values for crop growth and nitrate uptake is proposed as the basis for such a fault detection system. To this end, the Nitrate Control in Lettuce (NiCoLet) model was used to evaluate both short- and long- term changes in growth and nitrate accumulation. Three replicated experiments were conducted with lettuce (Lactuca sativa L. cv. Flandria), including: (1) plants subjected to either low or high nitrate concentration treatments for model calibration; (2) collection of growth data every 2 days for model validation; and (3) frequent (every 4molm−2 of accumulated light) collection of growth and shoot nitrate concentration data to validate short-term predictions. After a minor modification (maximum nitrogen uptake rate restricted) and calibration, the NiCoLet model accurately simulated lettuce crop growth and nitrate uptake on a long-term basis and provided evidence of short-term behaviour, including statistically significant predictions of diurnal patterns. This is a first step in realising fault detection systems based on mechanistic simulation models. [Copyright &y& Elsevier]

Water stress of a greenhouse crop results in a lower-than-normal transpiration and photosynthesis rates, which affects the humidity and CO2 concentration of the greenhouse air. This change may be detected and used for stress diagnosis if the signal-to-noise ratio is sufficiently large. Under midday conditions, when water stress is likely to occur, the greenhouse is often ventilated, resulting in a rather small signal-to-noise ratio. It is suggested here that the signal level may be increased by exciting the system, namely by suspending the ventilation for a short period of time. The transient response of temperature, humidity and CO2 concentration to the abrupt change of ventilation may be monitored, analysed and compared to a modelled normal response for the same greenhouse with an unstressed crop. A significant discrepancy between the two would indicate that the crop is stressed.Lawn, serving as a crop substitute, has been submitted to several irrigation–drought sequences in a small experimental greenhouse. Each day, in the early afternoon, ventilation was suspended for three periods of 30 min each. Differences in the response of CO2 concentration enabled the detection of all stress periods as soon as the rate of transpiration decreased to below normal. The humidity response was slightly less sensitive, and the temperature response was the least sensitive. Water-stress detection via the excitation method was considerably better than detection based on observations at full ventilation. [Copyright &y& Elsevier]

Estimating pesticide spray drift, which is a part of total drift loss, is complex as airborne pesticide concentrations are low and depend on multiple factors. The aim was to measure and compare vertical profiles of spray drift generated by different sprayers using Open Path Fourier-Transform-Infra-Red (OP-FTIR) spectrometer. Field tests included three types of commercial agricultural sprayers. The OP-FTIR was placed at the edge of an apple orchard with the line of sight parallel to tree rows. The OP-FTIR and its reflector were mounted on platform lifts to allow measurements at 4 heights: 3 (canopy height), 4, 5, and 6 m above ground. The sprayers sprayed water within the three tree rows closest to the OP-FTIR as well as outside each tree row in order to estimate the spray drift as function of distance with and without tree interference. The results of the experiments showed that, under the meteorological conditions prevailing, there were substantial differences between the sprayers in terms of spray drift of droplets with diameter > 5 μm. Additionally, the results showed that spray drift can be reduced substantially (by up to 50%) by using a tree-line barrier or a buffer zone. [ABSTRACT FROM AUTHOR]

In addition to ventilation, daily cooling must be provided for greenhouses located in semiarid climates to maintain the desired climate conditions for year-round crop production. High-pressure fogging systems have been successfully developed for greenhouse cooling. However the lack of control strategies, in combination with ventilation systems, especially passive ventilation, has limited their capabilities. A new cooling control strategy, which considered the contribution of humidification and cooling from the crop, was evaluated by computer simulations. The strategy controlled the amount of fog introduced into the greenhouse, as well as the percentage of vent openings to maintain desired values of greenhouse atmospheric vapour pressure deficit (VPD) and enthalpy, respectively, which would consequently affect air temperature. The performance was compared to constant fogging rate strategy, which was based on VPD. On average, the new strategy saved 36% water and consumed 30% less electric energy. Smaller air temperature and relative humidity fluctuations, and more consistent control, were achieved by varying the fog system operating pressure to provide a more optimum amount of fog for evaporative cooling. It was demonstrated by simulations that dynamically varying the fog rate and properly selecting the number of nozzles, savings of water and electric energy were increased, while still maintaining acceptable VPD and temperature. The improvements in the greenhouse climate achieved by the new strategy were due to its ability to dynamically manipulate fog rates, as well as, the vent configurations. [ABSTRACT FROM AUTHOR]